Paper ID #41259Pass-Fail Grading of Technical Writing in a Material Science LaboratoryProf. John R. Rogers, Benedictine College Dr. John Rogers is a member of the Benedictine College School of Engineering faculty where he teaches courses in mechanical engineering including materials engineering laboratory, mechatronics, vibrations, and design. He earned a doctorate in mechanical engineering from Rensselaer Polytechnic Institute in 2003. He has a range of engineering and teaching experience. As an ocean engineer, he developed towed systems for underwater listening, and structures that reduce ship noise. As a structural
Paper ID #37769The development of an artificial intelligence classifier to automateassessment in large class settings: Preliminary resultsProf. Euan Lindsay, Aalborg University Euan Lindsay is Professor of PBL and Digitalisation in Engineering Education at Aalborg University. His focus is the use of technology to flexibly support providing authentic learning experiences for stu- dent engineers. He is best known for his work as Foundation Professor of Engineering at Charles Sturt University.Mohammad Naser Sabet Jahromi, Visual Analysis of People Laboratory (VAP), Aalborg University Mohammad Sabet earned his Ph.D. in Signal
Paper ID #46677Student perspectives on attendance and instructional methods in a combinedlecture and laboratory courseKara Bocan, University of Pittsburgh Kara Bocan is an Assistant Professor in the Department of Electrical and Computer Engineering at the University of Pittsburgh. She received her PhD in Electrical Engineering from the University of Pittsburgh in 2017, and her BSE in Electrical Engineering and Bioengineering from the University of Pittsburgh in 2012. She currently teaches courses on data structures and algorithms, introductory programming, software architecture, and simulation and modeling. Her engineering
lab (Lichtenstein & Phillips, 2021).Significance of studyLaboratory experiences play an important role in connecting engineering students’theoretical concepts and practical knowledge (May et al., 2023; Yeter et al., 2023).Generally, the hands-on laboratory with machinery and a physical learningenvironment supports students’ active engagement during learning. However, the laterdevelopment of remote and virtual laboratories brings a more technology-basedexperimental environment. Student laboratories’ use experience and preferences areessential for current teaching methods and experimental environments' adaptivedevelopment. This study can provide students’ laboratory use experience andpreferences, the potential factors influencing their
load introduced by the presentation of an idea, and germane cognitive load is the effortrequired to convert knowledge from short to long term memory [17].Cognitive load is related to laboratory activities. At minimum, the presentation of laboratorymanuals can affect extraneous cognitive load. For instance, laboratory manuals that linkdiagrams to text poorly can introduce extraneous cognitive load [18]. Further, medical literatureshows some evidence that pursuing many learning goals can affect cognitive load [19].4 Teamwork, Interdependence, Stress and SpecializationTeam or group-based work benefits student learning [8], and teamwork skills are consideredessential to employment [20], [21], so teaching and learning teamwork is important
. ReferencesAgustian, H. Y., Finne, L. T., Jørgensen, J. T., Pedersen, M. I., Christiansen, F. V., Gammelgaard, B., &Nielsen, J. A. (2022). Learning outcomes of university chemistry teaching in laboratories: A systematicreview of empirical literature. Review of Education, 10(2), e3360. https://doi.org/10.1002/rev3.3360Alkhaldi, T., Pranata, I., & Athauda, R. I. (2016). A review of contemporary virtual and remote laboratoryimplementations: Observations and findings. Journal of Computers in Education, 3(3), 329–351.https://doi.org/10.1007/s40692-016-0068-zAltmeyer, K., Kapp, S., Thees, M., Malone, S., Kuhn, J., & Brünken, R. (2020). The use of augmentedreality to foster conceptual knowledge acquisition in STEM laboratory courses—Theoretical
Paper ID #48555WIP: Does this Course Need a Well-being Teaching Assistant?Jorge Baier, Pontificia Universidad Catolica de Chile He is an Associate Professor in the Computer Science Department and Associate Dean for Engineering Education at the Engineering School in Pontificia Universidad Catolica de Chile. His research interests are in Artificial Intelligence, Education and Wellbeing.Gabriel Astudillo, Pontificia Universidad Catolica de Chile Engineering Education Division and Computer Science Department, Pontificia Universidad Catolica de Chile.Carolina L´opez, Pontificia Universidad Catholica de Chile Carolina
wonderful and talented people at SCD’s Assessment and Research Laboratory to conduct research that informs and evaluates our practice of teaching and learning human-centered design in formal and informal learning environments. My Research focuses on studying students’ collaborative problem solving processes and the role of the teacher in facilitating these processes in STEM classrooms.Dr. Blake Everett Johnson, University of Illinois at Urbana - Champaign Dr. Blake Everett Johnson is a Teaching Assistant Professor and instructional laboratory manager in the Department of Mechanical Science and Engineering at the University of Illinois Urbana-Champaign. His research interests include experimental fluid mechanics
].Expectations for TAs:While research shows that TAs believe that content knowledge is the sole key to being aneffective teacher [14], students have a much different idea of what TAs should bring to the table.In a study of seven laboratory and lecture courses in environmental and water resourcesengineering, students were asked to rank what makes an effective TA from 17 categories ofintellectual excitement and interpersonal rapport developed by the American Society of CivilEngineers Body of Knowledge (ASCE-BOK) to describe effective teaching [22]. 21.3% ofstudents ranked fair grading practices as their first choice for what makes for an effective TAfollowed by explaining difficult concepts well (14.9%), coming to the classroom or laboratoryprepared (13.3
Paper ID #42444Why are we here? A Study of Student Perspectives on Attendance in a CombinedLecture and Laboratory CourseDr. Kara Bocan, University of Pittsburgh Kara Bocan is an Assistant Professor in the Department of Electrical and Computer Engineering at the University of Pittsburgh. Her primary focus is teaching with a secondary focus on engineering education research. She completed her PhD in Electrical Engineering and her BSE in Electrical Engineering and Bioengineering, both at the University of Pittsburgh. She currently teaches courses on introductory programming, data structures and algorithms, software
under the advisement of Dr. Catherine Berdanier in the Engineering Cognitive Research Laboratory (ECRL). In 2024, Erin was awarded the National Science Foundation Graduate Research Fellowship Program (NSF GRFP). She completed her B.S. in Mechanical Engineering at Tuskegee University and a M.S. in Engineering Design at Pennsylvania State UniversityCatherine G. P. Berdanier, The Pennsylvania State University Catherine G.P. Berdanier is an Associate Professor of Mechanical Engineering at Pennsylvania State University. She earned her B.S. in Chemistry from The University of South Dakota, her M.S. in Aeronautical and Astronautical Engineering and her PhD in Engineering Education from Purdue University. Her research
Paper ID #41990Design and Development of Survey Instrument to Measure Engineering DoctoralStudents’ Perceptions of Their Teaching PreparednessOmar Jose Garcia, University of Oklahoma Omar Garcia is an undergraduate Aerospace Engineering student at The University of OklahomaDr. Javeed Kittur, University of Oklahoma Dr. Kittur is an Assistant Professor in the Gallogly College of Engineering at The University of Oklahoma. He completed his Ph.D. in Engineering Education Systems and Design program from Arizona State University, 2022. He received a bachelor’s degree in Electrical and Electronics Engineering and a Master’s in
necessity, engineers must engage in learning throughout theircareer. Figure 5: Survey Response Frequency on Current Laboratory Learning Outcomes Figure 6: Survey Response Frequency on Past Positive Laboratory Learning OutcomesThe use of Kolb’s cycle in undergraduate engineering has been found to accomplish this mission[20]. Students in a mechanics course undertook a laboratory intended to teach how to derive amaterial’s yield strength. The students were given a combined torsion and bending apparatus andasked to derive equations for torque and moment. After graphing how these variables changedwith the deflection of the experimental apparatus, students measured the deflection of a sampleunder varying loading conditions. They then were
. Her research interests center on interdisciplinary learning and teaching, technology-integrated STEM teaching practices, and assessment development and validation in STEM education.Dr. Daniel S. Puperi, The University of Texas at Austin Daniel is an assistant professor of instruction in the Department of Biomedical Engineering at the Uni- versity of Texas at Austin. Dan received a BS in aerospace engineering from Purdue University and then worked at NASA Johnson Space Center for 15 years before pursuing a PhD in Bioengineering from Rice University. In 2016, Dan graduated from Rice and began teaching four design/laboratory courses required for all undergraduate BME students at UT Austin.Thomas E. Lindsay, The University
there are a myriad of reasonsthat instructors may decide to forgo live demonstrations, two common reasons for doing so arethat they doubt the effectiveness of live demonstrations, or that the time required to develop andimplement an effective demonstration prohibits instructors from utilizing them.As a result of the COVID-19 pandemic, instructors around the world were forced to adapt theircourses to be delivered remotely. While the vast majority of classes have returned to traditionalin-person formats, instructors retain the skills required to produce effective teaching videos. Ithas been shown that online laboratory activities can have some unique advantages [1]. Thispresents an opportunity for instructors to develop pre-recorded demonstration
live and video recorded). This paper describes a new classroom observationprotocol intended to monitor the focus (e.g., solo, pair, team, or whole class) and action (e.g.,discuss, speak/present, watch/listen, or distracted) of both students and teachers (instructors).The paper summarizes relevant background on evidence-based learning, student engagement,and classroom observation protocols, describes the development and structure of FASTOP,presents results from different pedagogies (e.g., lecture, laboratory, POGIL), and describeslessons learned and future directions. Results show distinctive patterns of student and teacherbehaviors for different pedagogies.1. IntroductionThe ICAP model describes the benefits of interactive (I), constructive (C
-school outreachprogram in engineering design for middle school students (ages 11-14), and how instructorsviewed the successes, challenges, and tensions of their students’ laboratory experiences. A challenge associated with NGSS and ASEE implementation is the meaningful integrationof science and engineering knowledge and skills in precollege teaching and learning. Researchhas identified issues that science teachers encounter with integrated STEM instruction, includinglack of relevant content knowledge, lack of administrative support, and weak self-efficacy inengineering pedagogy [4,10,11]. Research in STEM integration education has suggested thatinnovative instructional models and curricular resources are needed to demonstrate how scienceand
Engineering at California Polytechnic State University, San Luis ObispoJohn Galisky, University of California, Santa BarbaraDr. Brian P. Self, California Polytechnic State University, San Luis Obispo Brian Self obtained his B.S. and M.S. degrees in Engineering Mechanics from Virginia Tech, and his Ph.D. in Bioengineering from the University of Utah. He worked in the Air Force Research Laboratories before teaching at the U.S. Air Force Academy for sev ©American Society for Engineering Education, 2024 WIP: Instructors’ Framing of their Instructional PracticeIntroductionThis WIP study stems from a larger project focused on the propagation of educationaltechnology in diverse instructional settings
Conference & Exposition Proceedings, Portland, Oregon: ASEE Conferences, Jun. 2024, p. 48461. doi: 10.18260/1-2--48461.[8] I. M. Arsana, I. W. Susila, R. S. Hidayatullah, and S. R. Ariyanto, “Implementation of Troubleshooting Teaching Method to Develop Student’s Competency in Conducting Motorcycle Tune-up,” J. Phys.: Conf. Ser., vol. 1387, no. 1, p. 012096, Nov. 2019, doi: 10.1088/1742-6596/1387/1/012096.[9] S. Azizi and V. L. Fuentes, “Design and Development of a New Course and Laboratory: Solar PV Installation and Troubleshooting,” in Conference on Industry and Education Collaboration (CIEC), 2022. Accessed: Sep. 18, 2024. [Online]. Available: https://par.nsf.gov/servlets/purl/10332406[10] A. C. Sabuncu, M. V
is one of the difficult topics in thermodynamics. Due to its abstract concept andtheoretical nature, students could easily get lost during a typical PowerPoint lecture and found itdifficult to solve related problems in homework and exams. Even when students could follow thesteps to finish their homework, they felt challenged to connect the concept with real-lifeapplications. It showed that the passive learning format is not effective in teaching this subject. Toimprove the student learning, we added an active learning element in the lab portion of the courseby modifying some of the experiments. In many published conference papers, the active learninghas shown being effective in improving student learning. In this paper, we would like to
online, and in-person. The resulting data from approximately 200 consentingundergraduate mechanical engineering students in each of the synchronicity options (N > 600)showed that grades for certain lab experiences (i.e., early labs with high levels of skill-building)actually benefitted from an asynchronous online format, even above in-person offerings, while alater lab with deeper dives into specific skills produced better learning and ratings from studentswhen offered either in-person or synchronously online. The results of this investigation can benefitengineering educators, as well as those with interest in online physical labs in other disciplines.Keywords: Online Education, Laboratory Learning, Student ExperienceIntroductionSince the
blended project based learning (sbpbl) model implementation in operating system course. International Journal of Emerging Technologies in Learning (IJET), 15(5): 202–211, 2020.[19] Divya Kundra and Ashish Sureka. An experience report on teaching compiler design concepts using case-based and project-based learning approaches. In 2016 IEEE Eighth International Conference on Technology for Education (T4E), pages 216–219. IEEE, 2016.[20] Marc Dahmen, Luis Quezada, Miguel Alfaro, Guillermo Fuertes, Claudio Aballay, and Manuel Vargas. Teaching artificial intelligence using project based learning. Technical report, EasyChair, 2020.[21] D Anitha, C Jeyamala, and D Kavitha. Assessing and enhancing creativity in a laboratory course with
the Hokie Supervisor Spotlight Award in 2014, received the College of Engineering Graduate Student Mentor Award in 2018, and was inducted into the Virginia Tech Academy of Faculty Leadership in 2020. Dr. Matusovich has been a PI/Co-PI on 19 funded research projects including the NSF CAREER Award, with her share of funding being nearly $3 million. She has co-authored 2 book chapters, 34 journal publications, and more than 80 conference papers. She is recognized for her research and teaching, including Dean’s Awards for Outstanding New Faculty, Outstanding Teacher Award, and a Faculty Fellow. Dr. Matusovich has served the Educational Research and Methods (ERM) division of ASEE in many capacities over the past 10
-- and allowing it to guide one’s behaviorThe study of this domain focuses on determining what teaching practices produce the most positiveattitudes or connections to a concept and how feelings and behaviors change throughout theprocess of learning a concept/topic. This domain is harder to study and quantify since it is moreabstract compared to the cognitive domain. Also, it can be hard to separate positive feelingstowards the information and process of learning of a concept versus positive feelings created bygenerally positive social interactions during certain activities, such as during a laboratory session.Thus, our research aims to find general trends based on students' experiences, perceptions, and/orthoughts towards engineering classes and
60% ofstudents pursuing a major in a STEM degree in the US do not complete their degree [3].At the national level, it is evident that there is a need to change STEM education in order to bemore effective and accessible to all students [3]. A similar sentiment has been echoed by studentswho have indicated that their undergraduate engineering education experience could beimproved by changing teaching styles and techniques [4]. There is some indication that highereducation is beginning to implement a wide range of teaching practices and strategies (WATPS)[2]. Including a WATPS is not only beneficial for higher education in terms of attracting andretaining students but also for students and industry as a WATPS assists with preparing work-ready
naturally occurwithin social contexts (Lofland, 1971; Merriam & Tisdell, 2016). This approach assumes thatpeople’s values, attitudes, and behaviors are shaped by the social situation. Consequently,ethnographic researchers gather multiple types of qualitative data such as observations,interviews, and documentary evidence. This allows them to understand the context-dependentnature of people’s actions in naturalistic settings. Since the 1970s, educational research hasincreasingly adopted the ethnographic approach (Gordon et al., 2011; Green & Bloome, 2004).Its application spans various domains in education, including medical education (Reeves et al.,2013), second language teaching (Flowerdew & Miller, 1995), and social science education
Paper ID #37594IMPACT OF OPEN EDUCATIONAL RESOURCE ON IMPROVING LEARN-ING PERFORMANCE OFSTUDENTSDr. Atefe Makhmalbaf, The University of Texas at Arlington Dr. Atefe Makhmalbaf is an assistant professor at the UTA School of Architecture. She worked for Pacific Northwest National Laboratory (PNNL) as a research engineer and joined UTA after receiving a Ph.D. from Georgia Institute of Technology in Building Science. Dr. Makhmalbaf leads a Building Performance Analytics group at UTA. She develops decision support systems to enhance sustainable built environment. Since joining UTA, she has developed and taught several
[4]. This was found to better prepare students for lectureson new concepts, as well as give instructors more time to teach the new concept in class as theydid not need to review prerequisite knowledge with students [4]. Similarly, another study foundthat having more tutorials or example problems was helpful in engineering students'comprehension of math [12]. Other studies tested new e-learning practices and programs [5], [9-10]. They found that this style of learning was the best alternative during the COVID-19 pandemic;however, it also produced more confusion during certain laboratory activities [5], [10]. Recognizethat these studies were conducted before and during the pandemic, so newer studies may finddifferent results as online learning
barriers to conducting engineeringeducation research. We also hope to shed light on specific barriers that academic collaborationsshould be aware of, and ways academia can support industry in conducting engineeringeducation research.Key words: industry involvement, research-to-practice, educational technologyIntroductionSome engineering companies develop products that are used by academia in two ways. In thefirst case, the company’s core product might be an industry tool that is taught to students in orderto build their skills for future engineering careers. In these instances, the company may havetheir own educational division dedicated to providing students and instructors with resources forlearning with or teaching how to use the products. For
Paper ID #48147Democratizing the Analysis of Unprompted Student Questions Using Open-SourceLarge Language ModelsBrendan Lobo, University of Toronto An MASc candidate in the Integrative Biology and Microengineered Technologies Laboratory at the University of Toronto.Sinisa Colic, University of Toronto Sinisa Colic is an Assistant Professor, Teaching Stream with the Department of Mechanical and Industrial Engineering. He completed his PhD at the University of Toronto in the area of personalized treatment options for epilepsy using advanced signal processing techniques and machine learning. Sinisa currently teaches